Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193

Introduction. Over the past few decades, opioid abuse has become a major threat to public health. In 2013 alone, enough opioid prescriptions were written in the United States for every American adult to have their own bottle of pills. Since then, opioid prescribing rates and opioid related deaths have continued to grow, with over 46 people dying on average each day from prescription opioid overdoses in 2016. Orthopaedic surgeons are among the top 5 specialties in the number of opioid prescriptions written. For many common surgeries, such as total knee arthroplasty (TKA), post-discharge prescriptions are based on prescriber habits and opinion. There exists limited data-driven protocols to guide post-operative opioid prescribing practices. The purpose of this prospective study was to determine the average postoperative opioid consumption in patients undergoing primary TKA using a novel mobile text messaging platform. We hypothesized that majority of patients undergoing TKA do not properly dispose of left over pills after surgery. Methods. 95 patients undergoing primary unilateral TKA with one of nine arthroplasty surgeons at a single orthopaedic specialty hospital were prospectively enrolled. Daily pain levels and opioid consumption, and quantity and disposal patterns for left over medications were collected for six weeks following surgery using a novel mobile phone text messaging system. This system automatically queried patients twice a day, storing responses on a secure third-party host that investigators monitored and used to generate data reports in real-time. Results. Of the 95 patients enrolled, 1 was excluded for undergoing a secondary procedure in the acute postoperative data collection period. Of the remaining 94 patients, 88 (93.6%) completed the daily SMS surveys and were included in analysis. Average age was 62.0 ± 7.1 years, BMI 31.1 ± 6.2, and length of hospital stay 2.6 ± 1.2 days. The average oral morphine equivalents (OME) consumed during the 6 weeks post-surgery were 617.3 ± 350.26 mg, which corresponds to a mean consumption of 82 oxycodone 5 mg tablets per patient. For the 55(58.5%) of patients who had stopped taking opioids within 6 weeks of surgery, there were on average 196.2 mg OME left over, the equivalent of 26 oxycodone 5 mg tablets; 20% of those who stopped taking opioids had at least 367.5 mg OME left over, the equivalent of at least 49 oxycodone 5 mg tablets. Only 26.5% of patients with left over pills described an appropriate method of disposal of left over medications, with most patients storing left over pills in their homes. Conclusion. This prospectively collected data provides a benchmark for average opioid consumption after uncomplicated primary unilateral TKA. Many patients are prescribed more opioids than they require, and left-over medication is infrequently disposed of appropriately, which increases the risk for illicit diversion. Prospective collection of patient reported opioid consumption has tremendous value in the development of national postoperative guideline protocols while informing further research and strategies aimed to reduce opioid use and misuse and in predicting patient characteristics associated with increased opioid consumption after surgery

Aims

The Oswestry-Bristol Classification (OBC) is an MRI-specific assessment tool to grade trochlear dysplasia. The aim of this study is to validate clinically the OBC by demonstrating its use in selecting treatments that are safe and effective.

Aims

The aim of this study was to determine the general postoperative opioid consumption and rate of appropriate disposal of excess opioid prescriptions in patients undergoing primary unilateral total knee arthroplasty (TKA).